Shamma Nasrin

According to our database, Shamma Nasrin authored at least 15 papers between 2019 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2026

Machine learning calibration for radios.

Shamma Nasrin, Arindam Sanyal

Proceedings of the 44th IEEE VLSI Test Symposium, 2026

Residual Convolutional Neural Networks for Digital Calibration of Oversampled ADCs.

Shamma Nasrin, Matt Kinsinger, Anoop Bengaluru, Jia-Ching Chuang, Sumukh Prashant Bhanushali, Arindam Sanyal

Proceedings of the IEEE International Symposium on Circuits and Systems, 2026

2025

MOSAIC: Collaborative Compute-in-Memory µArrays for Flexible and Scalable Deep Learning.

Amit Ranjan Trivedi, Shamma Nasrin, Priyesh Shukla, Nastaran Darabi, Divake Kumar, Dinithi Jayasuriya, Nethmi Jayasinghe

Proceedings of the 43rd IEEE VLSI Test Symposium, 2025

From Signals to Features to Insights: Multi-Level Novelty Detection for Fast Scientific Discovery.

Devashri Naik, Nastaran Darabi, Sina Tayebati, Dinithi Jayasuriya, Shamma Nasrin, Danush Shekar, Corrinne Mills, Benjamin Parpillon, Farah Fahim, Mark S. Neubauer, Amit Ranjan Trivedi

Proceedings of the 43rd IEEE VLSI Test Symposium, 2025

Machine-learning based Blind Digital Calibration of Time-Interleaved ADC.

Sumukh Prashant Bhanushali, Shamma Nasrin, Debnath Maiti, Arindam Sanyal

Proceedings of the 43rd IEEE VLSI Test Symposium, 2025

2023

MC-CIM: Compute-in-Memory With Monte-Carlo Dropouts for Bayesian Edge Intelligence.

Priyesh Shukla, Shamma Nasrin, Nastaran Darabi, Wilfred Gomes, Amit Ranjan Trivedi

IEEE Trans. Circuits Syst. I Regul. Pap., February, 2023

Memory-Immersed Collaborative Digitization for Area-Efficient Compute-in-Memory Deep Learning.

Shamma Nasrin, Maeesha Binte Hashem, Nastaran Darabi, Benjamin Parpillon, Farah Fahim, Wilfred Gomes, Amit Ranjan Trivedi

Proceedings of the 5th IEEE International Conference on Artificial Intelligence Circuits and Systems, 2023

2022

ENOS: Energy-Aware Network Operator Search in Deep Neural Networks.

Shamma Nasrin, Ahish Shylendra, Nastaran Darabi, Theja Tulabandhula, Wilfred Gomes, Ankush Chakrabarty, Amit Ranjan Trivedi

IEEE Access, 2022

2021

MF-Net: Compute-In-Memory SRAM for Multibit Precision Inference Using Memory-Immersed Data Conversion and Multiplication-Free Operators.

Shamma Nasrin, Diaa Badawi, Ahmet Enis Çetin, Wilfred Gomes, Amit Ranjan Trivedi

IEEE Trans. Circuits Syst. I Regul. Pap., 2021

ENOS: Energy-Aware Network Operator Search for Hybrid Digital and Compute-in-Memory DNN Accelerators.

Shamma Nasrin, Ahish Shylendra, Yuti Kadakia, Nick Iliev, Wilfred Gomes, Theja Tulabandhula, Amit Ranjan Trivedi

CoRR, 2021

Compute-in-Memory Upside Down: A Learning Operator Co-Design Perspective for Scalability.

Shamma Nasrin, Priyesh Shukla, Shruthi Jaisimha, Amit Ranjan Trivedi

Proceedings of the Design, Automation & Test in Europe Conference & Exhibition, 2021

2020

Supported-BinaryNet: Bitcell Array-Based Weight Supports for Dynamic Accuracy-Energy Trade-Offs in SRAM-Based Binarized Neural Network.

Shamma Nasrin, Srikanth Ramakrishna, Theja Tulabandhula, Amit Ranjan Trivedi

Proceedings of the IEEE International Symposium on Circuits and Systems, 2020

2019

Supported-BinaryNet: Bitcell Array-based Weight Supports for Dynamic Accuracy-Latency Trade-offs in SRAM-based Binarized Neural Network.

Shamma Nasrin, Srikanth Ramakrishna, Theja Tulabandhula, Amit Ranjan Trivedi

CoRR, 2019

Towards Co-designing Neural Network Function Approximators with In-SRAM Computing.

Shamma Nasrin, Diaa Badawi, Ahmet Enis Çetin, Wilfred Gomes, Amit Ranjan Trivedi

Proceedings of the Fifth Workshop on Energy Efficient Machine Learning and Cognitive Computing, 2019

Low Power Speaker Identification using Look Up-free Gaussian Mixture Model in CMOS.

Alberto Gianelli, Nick Iliev, Shamma Nasrin, Mariagrazia Graziano, Amit Ranjan Trivedi

Proceedings of the IEEE Symposium in Low-Power and High-Speed Chips, 2019